Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Yutaka Nishino

dblp:40/3497 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Motion planning and robot control · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › manipulator motion planning
joint space path planning
0.012001
Image-Based Path-Planning Algorithm on the Joint Space · ICRA 2001
Robotics › Motion planning and robot control
path planning
0.012001
Image-Based Path-Planning Algorithm on the Joint Space · ICRA 2001
Robotics › Motion planning and robot control › motion planning › sensor-based motion planning
vision-based motion planning
0.012001
Image-Based Path-Planning Algorithm on the Joint Space · ICRA 2001
Robotics › Motion planning and robot control › robot control › sensor-based control
visual servoing
0.012001
Image-Based Path-Planning Algorithm on the Joint Space · ICRA 2001

Methods — techniques the papers use, named apart from their topics

sensor-based path planning · 0.0image-based heuristic · 0.0a* search · 0.0
YearPublicationVenuePosition
2001 Image-Based Path-Planning Algorithm on the Joint Space
abstract
To design an image-based path-planning algorithm, we should decrease the sum of moving distances of degrees-of-freedom of a manipulator. The algorithm A* selects the shortest path in the joint space by hard search. The combination search requires long distance moving. In a computer (virtual) world, the moving is not always time consuming. However in a real world, the moving is extremely time consuming. To overcome this drawback, we are seeking for a one-way search. For this reason, the sensor-based path-planning algorithms are preferred to an image-based path-planning algorithm. On the observation, we adopt a three or more dimensional sensor-based path-planning algorithm as the image-based path-planning algorithm. Its heuristics is defined by a difference between present and objective images. If the heuristics amounts to zero, the image-based algorithm stops. Therefore, convergence of a camera on a manipulator tip to an objective state is kept, and it is not influenced at all by uncertainties of robot and camera parameters.
Hiroshi Noborio, Yutaka Nishino
ICRA2